{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a4114b8a",
   "metadata": {},
   "source": [
    "### pandas可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ada448db",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2ed0bbdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Apple</th>\n",
       "      <th>Banana</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>39</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Apple  Banana\n",
       "0     30      51\n",
       "1     40      42\n",
       "2     20      33\n",
       "3     15      24\n",
       "4     18      15\n",
       "5     39      66"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1 = pd.Series([30, 40, 20, 15, 18, 39], name=\"Apple\")\n",
    "s2 = pd.Series([51, 42, 33, 24, 15, 66], name=\"Banana\")\n",
    "df = pd.DataFrame({\"Apple\": s1, \"Banana\":s2})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "19cc7f70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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spT4uhHvR2vjZbtLTuPaAC5EEfjV1msN9s+H+X6BSZfjpXvj+DqPEIoRwD6f3QepRp7502pVIAi+NZrfA6D9gwERI3gWfd4OFT8GFM2ZHJoQor3jL8Conv3jD5UgCLy3PStBpBIzfBp1GQsw0oz6+YQrk55odnRDCWnGW4VXV65sdSZlJAi+rqn7Q/z14bCM06gjLXoKpXSB+idTHhXA16UlwcptLlk9AErj1AkKN2vh9c0B5wMwh8MNdRj1NCOEa4qON25auMbyqJEng5dW8D4zZAFHvGr/Jp3aFRc/CxXNmRyaEuJb4xVA7BAJamh2JVSSB24KnF9wwBsZvh8hHYeu3MDkC/pwKBXlmRyeEuJycDGN4VUvXGV5VkiRwW6rmDwMnwpg/oEF7WPICfNYF9i8zOzIhREkJluFVLlr/Bkng9lG3FTzwKwybBboQfrwHpt8NKfFmRyaEKBJfNLyqs9mRWE0SuL0oBaFRxm7Ovm/D8S3Gajz6OamPC2G2gjzYvxRaRLnU8KqSJIHbWyVvY+7449ugw0Ow5Stj/vimL40JaEIIxzu2EbJTXbp8ApLAHadaHbj1Q2PiYf22sPj/4POukLDC7MiEqHjiF1uGV91kdiTlIgnc0eq3gQcXwNAfjQmH0++GGYPhzAGzIxOiYrg0vKqXyw2vKkkSuBmUMlqXxm6CPm/A0Q3w2Q2wZIIxk1gIYT+n9xrDq1xs9vflSAI3U6XK0PUJoz4ecR/8+ZkxX2XL11IfF8Je4iy7L1tEmRuHDUgCdwa+deH2yTBqLdRtDYuegS+6w8FVZkcmhPuJXwQNI11yeFVJksCdSeD18PBCGPwD5F6AH+6EmcPg7EGzIxPCPaSfhJPb3aJ8ApLAnY9S0Pp2GLsZbn4VDq81rga07GXITjM7OiFcW/xi4zbUNYdXlSQJ3Fl5+UD3p4354+FDjLnjk9vD1v9CYYHZ0QnhmuKjwa+JMU3UDUgCd3bV68Edn8LI1cYl3hY+CV/0MFbmQojSy8kwfm5CB7js8KqSJIG7igYR8MhiuOc7yE6HabfBT/fBucNmRyaEa0hY4fLDq0oqdQJXSnkqpbYrpRZa7ocopTYppRKUUrOUUt72C1MAxqoh7C4YtxluesXoUvm0Eyz/l5HUhRBXFhcNVfxcenhVSWVZgT8BFL/czHvAh1rrZsB5YLgtAxNX4VUFejwL42OgzSD442P4pANs+17q40JcTkEeHHD94VUllSqBK6WCgIHA15b7CrgJmGN5yjTgTjvEVyGlXczjjd/2Mnvr8as/sUYg3DUVRqwEvxBYMB6+7AVH/nBInEK4jGMbjS4uN2kfLFLaX0UfAc8B1S33/YFUrXXRdsFEoOHlvlApNRIYCdC4cWOrA60ItNYs2p3Eawv2ciYzBw8FDWtVoWuzOlf/woYd4NGlsOcXWP4qfDcAWt9hbNOvHeyQ2IVwanHRUMnH5YdXlXTNFbhS6lbgtNY6xpoTaK2/1FpHaq0jAwICrDlEhXAyNYt/TtvKuB+3E1jTh59Hd6FpgC/jZ27nRGrWtQ+gFLQdBOO2QO+X4MBymNIJVrxuvPsuREWltbH7skkv8K5mdjQ2VZoSSlfgdqXUEeAnjNLJx0AtpVTRCj4IOGGXCN1cQaHmuz8O02fSGjYcPMvLA1vx62M30jHYj88f6EBufiGPTY8hO6+UtW3vqtDzORi3FcLuhPWTjPr49hlQWGjX1yKEUzoVC6nHILS/aSHk5NvnvalrJnCt9Yta6yCtdTAwFFiptb4PWAUMsjztIWC+XSJ0Y3HJ6dw9dQOv/baXDsF+LHuqB//s3oRKnsY/S9MAXz4YHM7OxDRe/y22bAev2RD+8SUMXwE1G8H8x+Cr3nB0ox1eiRBOLD4aUNDCnAS+4eAZer+/mvhk2/8lXJ4+8OeBp5VSCRg18W9sE5L7y84rYOLSeG6dvJ5j5y7y0ZAIpj3SkUZ+Vf/23H5h9XmsV1Nmbj7OrC3Hyn6yRh1h+HL4x1eQeRr+GwU/P2KsSISoCOKjISjS2BTnYCkZOTzx0w58vD0Jql3F5scvUz+N1no1sNry8SGgk80jcnN/HjrLhLm7OXTmAv9o35CXB7bGr9rVW+if6RvK7hNpvDI/llaBNbg+qFbZTurhAdcPNmaQ/zHZaDuMj4Ybx0PXJ11+qL0QV1Q0vOrmVx1+6oJCzVOzdpCelcf3j3aiWmXbty/KTkwHSbuYxwu/7GLol3+SX6j5YXgnJg2OuGbyBvD0UHw8tB0BvpUZM30b5y7kWheEdzXo/SKM3wotb4W178OUSNj5k9THhXuKt8z+bun44VWfrUpgfcIZXrs9jFaBNexyDkngdqa1ZuGuk9w8aQ0/xyQyqkcTlj7Zg+7Ny9aR41fNmy8e6EBKZg6Pz9xOQaG2PqiaQTDoG3h0GVQPhF9HwTe3wPHN1h9TCGcUFw1+TaFOC4ee9s9DZ/lwxX7uiGjA0I6N7HYeSeB2VLw1sH7Nyswf25UXB7SiirenVcdr07Amb93ZhvUJZ5i4LL78ATbuDP/8He78HNJOwDd94Jd/Qlpi+Y8thNmy0y3Dq/o7dHjVGcsiK9i/Gm/f1RZlx3O7z55SJ1JQqPlh4xHeXxpPoYaXBrTika7Bl7pLymNwZCN2HE9l6uqDhAfVIqpNOa8q4uEBEcOg1W3wx0ew4RPYt9C41FvXJ4y2RCFcUcIKKMxzaPmk0FL3Ts3K47tHOuFrh7p3cbICt7H45AwGfW60Bra/rjbLnurBiB5NbJK8i7x6W2siGtXi2Z93knA60zYHrewLN71sbAQKjYI17xr18V2zjY0QQria+MVQ1d+hw6umrjnIugNnePW21rRuYJ+6d3GSwG2kqDVw4OR1HD17kQ+HhPP9o50u2xpYXpUreTL1/vZUruTB6OkxZObY8ALItRobI2sfWQLVAmDuCKO0kmjVRlwhzFF8eJWHdSXLstp8+BwfLIvntvAG3NvJMWNDJIHbwJ+HzjLg43VMWZXA7eENWPF0T+5qF2TX2ldgzSp8cm87DqVk8tycnWhbr5Kv6wIjVhkXk0g9Bl/fBHNHGW1ZQji7oxuM4VUOmv191lL3buxXlXfuamPXn/3iJIGXQ1pWHi/ONVoD8woL+f7RTkwaUrrWQFu4sWkdXujfkujdyXy17pDtT+DhAe3uN8bWdnsaYn81tuWv+Q/klWI+ixBmiS8aXtXb7qcqLNQ8PXsn5y7kMuXe9lT38bL7OYtIAreC1pro3UncMmkNs7YcZ6SlNbBHC8cP6xrRvQkD2wby7uI4NiScsc9JKleHW141LiTR7BZY9TZM6WhMP5T6uHA2Whvtgw4aXvXF2kOs2Z/CK7e1pk3DmnY/X3GSwMsoKS2LEd/H8NiMbdStXpkF47oxYUArqnqb09CjlOK9QdfTJMCXcTO3c7I0kwutVTsYhvwADy+CKrVgzqPwbRSc2Ga/cwpRVqf2QNoxh5RPthw5x8Rl8QxsG8j9nR0/LlsSeCkVFmq+33iEPpPWsj4hhQkDWjJ/bFeH/8a9HN/KlfjCMrlwzIxtdpt8dklwNxi5Bm7/BM4dNIZkzXsM0pPse14hSiN+MaDsPn3w3IVcHp+5naDaVfj33fbt974SSeClsP+U0Rr4r/mxtGtci2VP9mRkj6Y2bQ0sr6YBvky8J5ydx1N5bcFe+5/QwxPaPwjjtxn94rt/NurjaydCXrb9zy/ElcQtgqCO4FvXbqcoLNQ8M3sHZzNz+fTe9tRwYN27OOfJQE4oO6+AScuM1sDDZy4wabDRGtjY3zk3t0S1qc+YXk2ZufkYs7dc43JstuJTw7jyz9hNxhtGK9+ETztC7DypjwvHSzsBSTvsfum0r9YdYlV8Ci/f2srUv8JlJ+YVbD58jhfm7uJQygX+0a4hLw1shb9vZbPDuqZn+4ayOzGNl+fvoWVg9bJPLrSWXxMYOgMOrYGlE+Dnh+C6rhD1bwgMd0wMQhQNrwq13+7LmKPn+M/SeAa0rc8DN1xnt/OUhqzASzBaA3cz+IuN5BX8rzXQFZI3GJMLJw+zweRCazXpCaPWwq0fQkocfNET5o+FjFOOjUNUTPFFw6ua2+Xw5y/kMv7H7TSsVYV3777elLp3cZLALbTWLN6dRJ9Ja5i15ZiprYHl5VfNm6n3t7fN5EJreHhC5KNGfbzLWNg5y6iPr/8Q8nMcG4uoOLLT4PA6o3xih8SqtebZn3eSkpnDlHvbmVb3Lk4SOP9rDRwzYxsB1Sszf6y5rYG2cH1QLd68I4z1CWf4wBaTC61RpRb0e9uoj4d0hxWvwaedYO8CqY8L20v43RheZafyydfrDvN73GleGtDKcaXJa3DdDGUDhYWa6ZuO8p8l8eQXFvJi/5YM7xbiVN0l5TGkY2N2HE/ls9UHCW9Ui35h5ZxcaC3/pjBsJhxcCUsmwOwHILi7UR+v39acmIT7iY+GqnWgke0vFLbt2HneWxJHVFh9Hrox2ObHt5Z7ZCorFG8NjGhktAaO6ulcrYG28NrtYYQH1eSZ2Ts5mGKjyYXWanoTjF4PAyYaVwr/vDsseBwyU8yNS7i+gjw4sMwuw6tSLxp17/o1fXhvkPl17+LcK1uVQk7+X1sDP7gnnB+GO29rYHkZkws74F3Jg9E/xHDBlpMLreFZCTqNgMe3wQ1jYMcM+KS9ca3OfAe/4Srcx9E/jBq4jdsHjbr3Lk5nZPPpve2pWcX8undxFSqBbz58jv4fr2PyygQGtg1kxdM9ubuDfacGOoMGtaowZVg7DqZk8tycXbafXGiNKrWNEsqYjdC4Cyx/BT7rbGzCcIb4hGuJswyvatLLpof9Zv1hVuw7xQv9WxHeqJZNj20LFSKBF28NzM0vZNqjnfhoaDuXaQ20hRub1eG5qJYs2p3E1+sOmx3O/wS0gPtmw/2/gIcX/HQvfH+HUWIRojS0NurfTXrbdHjVjuOpvLckjj6t6/Fo12CbHdeW3D6BL9nzv9bAf3YLYdlTPejpgq2BtjCqRxP6t6nPu0vi2HjwrNnh/FWzW2DMH9D/fUjaCZ93g4VPwQU7TVgU7uPUHkg7btPySdrFPMbO2Ebd6j5MHBTutH+lu20CT07LZuT3Wxk9fRt1fCszb2xXXr61tUu3BpaXUor37wkn2L8q437cRlKak8309vSCziPh8e3QcQTETIPJ7WHjp1IfF1cWFw0o4w1MG9Ba839zdnIqPZsp97ajZlXnqnsX53YJvLBQ88OfR+kzaQ1r9qfwQv+WzB/X1Wn6Ns1mTC6MJDuvgDHTHTC50BpV/WDAf+CxjdCoo7E1f2oXiF8i9XHxd/GLjNZBGw2v+m7DEZbtPcUL/VvSrnFtmxzTXtwqgR84lcHgLzbyyrw9XN+oJsue6sHonk3xcrPWwPJqVteYXLjjeCpv/OaAyYXWCgg1auP3/gwomDkEpv8DTu8zOzLhLNISjZKbjWZ/7zyeyjvR+7ilVV2GdwuxyTHtyS0yW05+AR8u38+AyetISMlk4j3hTB/emev87X81DlfVv20go3o2YcamY/y81UGTC63Voq+xGo96F07EwNSusOhZuHjO7MiE2eIXG7c2SOBpWXmMm2mpe9/jvHXv4ly+ILzlyDlenLubhNOZ3BHRgFdubU2dCtRdUh7/Z5lc+NK8PbQKrOEUF6e4Ik8vo2+87WBY/Q5s/caYQd7rReg43Pi8qHjiFoF/M6ObqRy01jw/ZxdJqdnMGtWFWlUdc13b8nLZFXh6dh4v/bqbez7fSFZuAf99pCMfD20nybsMKnl68MmwdtSp5s2oH2I47+jJhdao5g8DP4DRf0CDdrDkeZh6IxxYbnZkwtGy0+DIepusvr/feJQlsck8FxVKh+ucu+5dnEsm8CV7kukzaQ0zNxutgcuf7kHvUPtdfcOd+ftWZur9HUjJyOHxn0yYXGiteq3hgV9h2E9QWAAzBsH0QZBi0uAu4XgJK4zhVS3LN7xqd2Iaby/ax80t6/LPbk1sFJxjXDOBK6V8lFKblVI7lVKxSqnXLY+HKKU2KaUSlFKzlFJ2/5sjOS2bUT9sZfT0GPyrSWugrYQ3qsXrd4Sx7sAZPly+3+xwSk9Zrnv42J/Q9204vhk+6wKLn5f6eEUQZxleFdTR6kOkZ+cx9sdt1PH1ZuI94Xh4OH/du7jSrMBzgJu01uFABBCllLoBeA/4UGvdDDgPDLdXkMVbA1fHS2ugPQzr1JghkY2YsiqBZbHJZodTNpW84cZxxnyV9g/C5i+N+Sqbv4ICk2e/CPsoyDPKZqHWD6/SWvPCL7s4kZrFJ/e2o3Y116h7F3fNBK4NRWPsvCz/aeAmYI7l8WnAnfYIEGDkD1ulNdABXr8jjOstkwsPmT250BrV6sBtH8GodcaY2uhn4fOuxpxo4V6OrIectHLVv6f/eZTo3cn8X79QOlznZ8PgHKdUWVAp5amU2gGcBpYDB4FUrXXR8iYRaHiFrx2plNqqlNqakmLd2NBbr2/A+4Oul9ZAO/Px8uSz+9pTyVMxeroTTC60Vv028OACGPqjcQWg6f+AH4fAmQNmRyZsJT4aKlUx5p9YYc+JNN5cuI9eoQGM7O5ade/iSpXAtdYFWusIIAjoBLQs7Qm01l9qrSO11pEBAdbNILmzXUPuiWzkEn2Zri6odlU+GdaehNOZPP+Lk0wutIZSxptbYzdBnzfgyB/w2Q3GBSWyUs2OTpSH1kb/d9Pe4F32MdAZlrq3XzVvJg2OcLm6d3FlqkNorVOBVUAXoJZSqujdwyDghG1DE2bp1rwOz/YLZeGuJL5Z70STC61RqTJ0fcKoj0fcB39+ZtTHt3wj9XFXlbzbGF5lRflEa82Lc3eTeN6oe/u5YN27uNJ0oQQopWpZPq4C9AH2YSTyQZanPQTMt1OMwgRjejalX1g9/r04jj8POdnkQmv41oXbJ8OotRDQChY9DV90h0OrzY5MlFW89cOrZmw6xsJdSTzTtwUdg12z7l1caVbggcAqpdQuYAuwXGu9EHgeeFoplQD4A9/YL0zhaEopJhabXJiclm12SLYReD08vBAG/wC5F4zZ4zOHwdmDZkcmSituETTqDL5lK8nGnkzjjYV76dkigNE9mtopOMcqTRfKLq11O6319VrrNlrrNyyPH9Jad9JaN9Na36O1zrF/uMKRqvt48cUDHcjKLWDMjBhy8wvNDsk2lILWt8PYzXDzq3B4LXzaGZa9bOzuE84r9Tgk7yrz7O/MnHzG/bid2lW9mDTY9fq9r0R68cRVNatbnffvCWf7sVTeXOjEkwut4eUD3Z+G8TEQPgQ2TDHmj2/9r7G7UzgfK4ZXaa2ZMHc3R89eYLKbXYlLEri4pgFtAxnVowk//HmUOTGJZodje9Xrwx2fwshVUKc5LHwSvugJh9eZHZkoKT4a/Jsb/06lNHPzcRbsPMkzfUPp3MTfjsE5niRwUSr/1y+ULk38eenX3ew54aZlhgbt4JHFcM93Rill2q3w031wzsU7cdxF0fCqMpRP9p5M57XfYunevA5jerpH3bs4SeCiVCp5elxquxo93UUmF1pDKQi7C8ZthptehoOr4NNOsPxVyE43O7qK7cByY3hVaOmGVxl1723UquLFh0Ncu9/7SiSBi1KrY5lceDo9hydm7XCdyYXW8KoCPf7PqI+3GQR/fASfdIBt30t93Czx0VAtAIIir/lUrTUv/7qbI2cvMHmY+46ZlgQuyiSiUS1euz2MtftT+GiFC00utFaNQLhrKoxYCX4hsGA8fNnL2NkpHCc/11iBtyjd8KrZW48zb8dJnrylBTe4Wd27OEngosyGdWrE4MggPlmZwPK9p8wOxzEadoBHl8Ld3xijar8bALMfhPNHzI6sYji6HnLSS9V9Epeczr/mx9KtWR3G9m7mgODMIwlclJlSijfuaEPbhjV5etYODp+5YHZIjqEUtB0E47ZArwnGinBKJ1jxOuRkmB2de4tfbBle1euqT7uQk8/YGduoYal7e7ph3bs4SeDCKj5enky93zK58IcYLuZWoLki3lWh1/MwbiuE3QnrJxn18e0zoNBNNjs5E62Nizc0vemqw6u01rwybw+Hz1zg46ERBFR3z7p3cZLAhdWCaldl8rB2HDidwfO/7HbdyYXWqtkQ/vElDF8BNRvB/Mfgq95wdKPZkbmX5F2QnnjN9sGfYxKZu/0Ej9/cnBub1nFQcOaSBC7KpXvzAJ7pG8pvO0/y7R9HzA7HHI06wvDl8I+vIPM0/DcKfn4EUo+ZHZl7iIsG5XHV4VX7T2Xwr/l7uLGpP+NvKv0mH1cnCVyU22O9mtK3dT3eid7HJneYXGgNDw+4fjCM3wo9nzda3qZ0hJVvGUOzhPXiLcOrql1+VX0xN5/HZmzDt7IXHw11/7p3cZLARbkppfhgcDjX+VVl7I/bOZXuJpMLreFdDXpPMOrjLW+Fte8b9fGdP0l93Bqpx4z536H9r/iUV+bFcjAlk4+HRlC3uo8DgzOfJHBhE0WTCy/m5jNmuhtNLrRWrUYw6Bt4dBlUD4RfR8E3t8DxzWZH5lrilxi3V9h9OScmkV+2JTL+puZ0bVYx6t7FSQIXNtO8XnXeHxTOtmOpvLXIzSYXWqtxZ/jn73Dn55B2Ar7pA7/8E9LccCiYPcQvgjotoM7f+7kPnMrglXl7uKGJH0/cXHHq3sVJAhc2NfD6QEZ0D+H7jUeZu02SFGDUxyOGGdvye/wf7PsNPomEVf+G3ItmR+e8slKN4VWX2byTlVvA2B+3Ua2yJ5OHtqtQde/iJIELm3s+qiU3NPHjxbm7iT3pppMLrVHZ1xiQNW4LhEbBmndhSiTsmm30Oou/SlgBhfnGxalLeHXBHg6czuTDIRHUrVGx6t7FSQIXNlfJ04Mp97andlVjcmHqRTedXGitWo2NkbWPLDE6K+aOMEoriTFmR+Zc4hYZw6sa/nV41dxticzemsi43s3o3rxsl1VzN5LAhV3U8a3MZ/e3Jzktmydn7aDQnScXWuu6LjBitXExidRj8PVNMHcUpJ80OzLz5ecaK/AWUUYJyiLhdAYv/bqHTiEVt+5dnCRwYTftG9fm1dvCWB2fwke/HzA7HOfk4QHt7jfq492ehthfjbbDNf+BvCyzozNP0fCqYuWTrNwCxs7YTlVvTz4Z1o5KnpK+5Dsg7Oq+zo0Z1CGIyb8f4Pd9FWRyoTUqV4dbXjUuJNHsFlj1trERaM8vFbM+HhcNXlX/Mrzq9d9iiT+VwaQhEdSrwHXv4iSBC7tSSvHWnW1o07AGT87awZGKMrnQWrWDYcgP8PAiqFIL5jwK30bBiW1mR+Y4WhvTB5veZFxYA5i3/QQ/bTnO2N5N6dmiYte9i5MELuzOx8uTqfd1wNNDMXp6BZtcaK3gbjByDdw2Gc4dNIZkzXsMMpLNjsz+knYaw6ss7YMHUzKZ8OtuOgX78dQtLUwOzrlIAhcO0civKpOHtiP+VAYvzq2Akwut4eEJHR6C8dug6xOw+2eY3B7WToQ8Nx5XEF80vKof2XkFjJ2xDR8vTz4eFiF17xLkuyEcpkeLAJ7p04L5O07y3YYjZofjOnxqQJ83YOwmaNobVr4Jn3aE2HnuWR+Pi740vOr13/YSl5zBpMHhBNasYnZkTkcSuHCox3o145ZW9Xh70T62HDlndjiuxa8JDJ0BDy6AyjXg54fgu4FGycFdpB6DU7shdADzd5xg5uZjjOnVlF6hdc2OzClJAhcO5eGhmDQknEZ+VXlsxjZOV+TJhdZq0hNGrYVbP4SUOPiiJ8wfCxlu0OUTvxiAY3V7MWHubiKvq80zfaTufSWSwIXD1fDx4vP7O5CZbcxxrvCTC63h4QmRjxr18S5jYecso398/YeQn2N2dNaLW0RhnRaMik7Du5IHk6Xf+6rkOyNMEVq/Ov8ZdD1bj57nneh9ZofjuqrUgn5vG/XxkO6w4jX4tBPsXeB69fGsVDj6B+s8OrEvKZ1JgyNoUEvq3ldzzQSulGqklFqllNqrlIpVSj1hedxPKbVcKXXAclvb/uEKd3JbeAOGdwvhuw1H+HW7TC4sF/+mMGwmPPCrcfX22Q/AtNuMiyG4igPLoTCfj443Z1TPJvRuKXXvaynNCjwfeEZr3Rq4ARirlGoNvAD8rrVuDvxuuS9EmbzQvyWdQozJhXtPppsdjutrehOMXg8DJsKpWPiiB/z2BGSmmB3ZNV3YNZ8zuiaejSJ5tm+o2eG4hGsmcK11ktZ6m+XjDGAf0BC4A5hmedo04E47xSjcmJenB5/e256aVbwYPT2Gs5kuXL91Fp6VoNMIeHwbdB4N26fDJ+3hj8nGkCgnlJ2dhUpYwRoVycf3dsBL6t6lUqbvklIqGGgHbALqaa2TLJ9KBurZNjRRUQRUr8xn93UgKS2LLv9eySP/3cxPm49xRpJ5+VSpDVH/hjEboXEXWP4KfNbZGNPqZPXxWT//SFWyaNptMA2l7l1qqrQ74pRSvsAa4G2t9VylVKrWulaxz5/XWv+tDq6UGgmMBGjcuHGHo0eP2iRw4X5iT6Yxb/sJlsQmc/xcFh4KIoP9iAqrT9+wegTVrmp2iK4tYQUsmQBn4iGkp5Hc64WZHRXRu5M4M2s8Q73X4f3ikUvzT8T/KKVitNaRf3u8NAlcKeUFLASWaq0nWR6LB3pprZOUUoHAaq31VQtXkZGReuvWrVa9AFFxaK3Zm5TO0thTLN2TTPypDADaNKxBVFh9otrUp1nd6iZH6aIK8mDrt7DqHWNca4dHoPcE48ISJjh69gK3Tl7HKs+x+DW/AY9hM0yJw9lZncCVUgqjxn1Oa/1kscffB85qrd9VSr0A+Gmtn7vasSSBC2scPnOBpbHJLI1NZvuxVACaBFQjKqw+/cLqc31QTYz/TUWpXTwHq9+FLV+Dty/0eh46joBK3g4LISe/gLunbsD37B5+4gW4cypE3Ouw87uS8iTwbsA6YDdQtONiAkYdfDbQGDgKDNZaX3VvtCRwUV7Jadks35vMkthk/jx0joJCTYOaPvS1JPOOwbVl40dZpMTD0glGecW/GfR9G1r0Awf8QnxtQSzfbTjCyvZ/0GTfVHg2Aar52/28rqhcJRRbkQQubCn1Yi4r9p1maWwya/enkJNfSO2qXvRpXY9+YfXp2qwOPl6eZofpGvYvMxL52QNGK2K/f0PdlnY73eLdSYyZsY3h3UJ45fhI44IWjy622/lcnSRw4dYu5uazJj6FJbHJrNx3moycfKp5e9KrZV2iwurTu2VdfCtXMjtM51aQZ5RUVv8bcjKh43Do9SJU9bPpaY6dvcjAT9bRJMCXn4c0xHtKOPR9C24cb9PzuJMrJXD5P1q4harelejfNpD+bQPJzS9kw8EzLI09xfK9ySzalYS3pwfdmtehX1g9bmlVD3/fymaH7Hw8veCGMdB2MKx+x0jmu2YbSbzjcOPz5ZCSkUPsyTQ+WLYfBUwZ1g7v/d8bn7RcvEGUjazAhVsrKNRsO3aeJXuMN0ETzxvtiR2D/YhqU5++YfWl7/hKTu01yiqHVkGdFtDvHWje55pfprXm2LmLxJ5MJ/ZkGntPphN7Mp3TGUZfv5en4tN729M3rL6x3T/ztDHLRVyRlFBEhae1JvZkOstijTdB95/KBOD6oJr0s7wJ2qyur8lROhmtYf8SWPqScWm3Zn2MRB5gjHjNKygk4XTmpWQdezKdfSfTycgxLpvn6aFoXteX1g1qENagJmENatAqsAY1q3hB1nn4T1PjakO3vGrmq3R6ksCFKOFQSqbRax6bzI7jqQA0DahGVBsjmbdtKO2Jl+TnkrvxczzW/QePvCw2+N3Jp4WDiEnh0jjgKl6etAysTlixZN2iXvUrv5G8azbMHQHDV0Cjjg58Ma5HErgQV5GUlsXyvadYsieZTYeN9sSGtarQp3U9otrUp2OwH54eFSeZn7uQe2lFXbS6PnzmArV1Os9U+pmhlVZy0cOXDY1GkRP+IK2D/AmpU61s36OfH4ajG+DpOPCQ1s+rkQQuRCmdv5DLin2nWBp7irUHUsjNL8Svmjd9WtWjX5t6dG1Wh8qV3KM9UWtN4vksYk+ms/dkGnuTjISdlPa/KyU1rFXFUgL538o6MDsBtXQCHF4LAS2Nskqzm0t/4vwco3zS5h9w+2Q7vDL3IglcCCtcyMlnzf4UluxJZlWc0Z7oW7kSvUIDiGpTn16hrtOemF9QyKEzF4yV9QkjUe9NSictKw8ADwVNA3z/kqhbN6hBrapX2J2ptTEYa9nLcP4wtIgyNgLVaXbtYBJWwPS74d7ZxsYhcVWSwIUop5z8AjYcPMuy2GSWxZ7i7IVcvCt50L1ZHfqF1eeW1vXwq+a4rehXk5VbQFxy+qUSyN6TacQlZ5BjqVdXruRBy/rVaW1J1GENatCyfg2qeFvxl0V+Dmz6HNa8D/lZ0GkU9HzOuFrQlSx8Gnb+BM8dAi8f615kBSIJXAgbKijUbD1y7tKboCdSjfbETiFF0xPrO+xyYKkXcy+16hXVrQ+mZFJo+dGu4VPp0oo6rKGxum5Sp5rtRw5knoaVb8G2743NP71fgvYPGfPJi9MaJrWGoA4wZLptY3BTksCFsJOi9sSiXvMDp432xPCgmvSzdLQ0DSh/e6LWmqS07L8k6r0n0zmRmnXpOYE1fWgdWMNS/jCSdlDtKo7tpknaBUtehKProW4YRL0DTXr97/MntsFXvWV4VRlIAhfCQQ6mZBrTE/ckszMxDYDmdX3pZxmFG9agxjUTakGh5rClXl18dX3+olGvVgpC6lT738q6QQ1aB9Zwnh2mWsO+BUZ9PPUYhA6Evm8a1+5c+TasmyjDq8pAErgQJjiZmsWy2GSWxp5i0+GzFGqjq8PYOFSPyGA/8goK2X8q4y87F/clZZCVVwCAt6cHLer7EhZY01ICMerV1VzhzdO8bPjzM1j3gVErv2G0cfHiqv7wSLTZ0bkMSeBCmOxcUXvinmTWJZwhN7+QGj6VuJhbQL6lYF29ciValWjZa1bX1/WvEZmRDL+/CTtmANroVrlxnNlRuQxJ4EI4kcycfFbHn2bd/jPUqe59KVk3ql0VD3feMHRyu9F90vN5m085dGeSwIUQwkVdKYG7+N9lQghRcUkCF0IIFyUJXAghXJQkcCGEcFGSwIUQwkVJAhdCCBclCVwIIVyUJHAhhHBRDt3Io5RKAY5a+eV1gDM2DMcVyGuuGOQ1u7/yvt7rtNYBJR90aAIvD6XU1svtRHJn8porBnnN7s9er1dKKEII4aIkgQshhItypQT+pdkBmEBec8Ugr9n92eX1ukwNXAghxF+50gpcCCFEMZLAhRDCRblEAldKRSml4pVSCUqpF8yOx96UUt8qpU4rpfaYHYsjKKUaKaVWKaX2KqVilVJPmB2TvSmlfJRSm5VSOy2v+XWzY3IUpZSnUmq7Umqh2bE4glLqiFJqt1Jqh1LKple0cfoauFLKE9gP9AESgS3AMK31XlMDsyOlVA8gE/hea93G7HjsTSkVCARqrbcppaoDMcCdbv5vrIBqWutMpZQXsB54Qmv9p8mh2Z1S6mkgEqihtb7V7HjsTSl1BIjUWtt845IrrMA7AQla60Na61zgJ+AOk2OyK631WuCc2XE4itY6SWu9zfJxBrAPaGhuVPalDZmWu16W/5x7NWUDSqkgYCDwtdmxuANXSOANgePF7ifi5j/cFZlSKhhoB2wyORS7s5QSdgCngeVaa7d/zcBHwHNAoclxOJIGlimlYpRSI215YFdI4KKCUEr5Ar8AT2qt082Ox9601gVa6wggCOiklHLrcplS6lbgtNY6xuxYHKyb1ro90B8YaymR2oQrJPATQKNi94Msjwk3YqkD/wLM0FrPNTseR9JapwKrgCiTQ7G3rsDtlprwT8BNSqnp5oZkf1rrE5bb08CvGGVhm3CFBL4FaK6UClFKeQNDgQUmxyRsyPKG3jfAPq31JLPjcQSlVIBSqpbl4yoYb9LHmRqUnWmtX9RaB2mtgzF+jldqre83OSy7UkpVs7wxj1KqGtAXsFl3mdMncK11PjAOWIrx5tZsrXWsuVHZl1JqJrARCFVKJSqlhpsdk511BR7AWJHtsPw3wOyg7CwQWKWU2oWxSFmuta4QbXUVTD1gvVJqJ7AZWKS1XmKrgzt9G6EQQojLc/oVuBBCiMuTBC6EEC5KErgQQrgoSeBCCOGiJIELIYSLkgQuhBAuShK4EEK4qP8HH5j3zCZ12O4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b478bdb5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# s1.plot(kind=\"图类型\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de842622",
   "metadata": {},
   "source": [
    "### 使用pandas绘图时, 默认索引就是X轴坐标，各个值为Y坐标\n",
    "'''\n",
    "s1.plot(kind=\"图类型\")\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1d2f3da5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "783fc813",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SXA18uKpuXmHdx6rqd2cQayySbKU/S71/hXXnVtW/zCDW2CR5UlU9ssL4GcCWqrpjBrEmIsmFwLlV9fZZZ5m0JE8FNlfVd2aWYaMUuCT9tPE6cElqlAUuSY2ywCWpURa4JDXKApekRv0vZ7TJP1In9eYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s1.plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6c3c3621",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    30\n",
       "1    40\n",
       "2    20\n",
       "3    15\n",
       "4    18\n",
       "5    39\n",
       "Name: Apple, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s1.plot(kind=\"pie\", figsize=(4, 4))\n",
    "s1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "62897c0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s1.plot.bar(figsize=(4, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "101564b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "546247d7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
